shamimtowhid/Early-Intrusion-Detection-in-SDN

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shamimtowhid/Early-Intrusion-Detection-in-SDN

shamimtowhid

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This project aims to detect intrusion in an SDN network as early as possible.

encrypted_network_traffic_classification_in_SDN

This repository describes the demonstration of encrypted network traffic classification in SDN environment. A testbed is created using Mininet in this project. A RYU controller application is developed to classify network traffic in real-time.

Spectrogram-segmentation-for-bird-species-classification-based-on-temporal-continuity

This repository contains all the python script that is used to do a thesis on bird species classification using their recorded audio signal.

traditional_ML

This is a python package that contains various traditional machine learning algorithms.

Jupyter Notebook

int_p4

This project aims to develop network-based intrusion detection system using ML models. We use data plane programming to collect features and deploy our ML model in the data plane insteaded of control plane.

5G_cloud_deployment

This repository is an initiative to automate the deployment process of 5G core network in cloud environment.

Implementing-K-Means-Clustering

the objective of this experiment is to understand one of the very popular clustering algorithm known as K-Means clustering algorithm. This is an unsupervised learning method which means the class label is unknown here. But to measure the performance of the algorithm we need to know the ground truth. Here in this experiment we will use cluster purity as performance measure of the classifier. Here we use the dataset that has 150 data with four dimension each. We will cluster the whole dataset into three cluster here, so in our experiment k=3.